Timeline for Analysis strategy for rare outcome with matching
Current License: CC BY-SA 3.0
7 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Dec 12, 2016 at 12:07 | comment | added | Frank Harrell | I find this argument not convincing. Matching on continuous variables results in an incomplete adjustment because the variables have to be binned. Matching throws away good data from observations that would be good matches. Extrapolation bias is only a significant problem if there is a covariate by group interaction, and users of matching methods ignore interactions anyway. If you don't want to make regression assumptions that are unverifiable, remove observations outside the overlap region just as with matching. | |
| Dec 12, 2016 at 9:00 | history | edited | Arne Jonas Warnke | CC BY-SA 3.0 |
Response to comment of Frank Harrell
|
| Dec 11, 2016 at 16:11 | comment | added | Frank Harrell | I don't see why matching plays a role here. | |
| Dec 10, 2016 at 10:38 | history | bounty ended | CommunityBot | ||
| S Dec 2, 2016 at 14:59 | history | suggested | user22 | CC BY-SA 3.0 |
corrected code entry
|
| Dec 2, 2016 at 14:56 | review | Suggested edits | |||
| S Dec 2, 2016 at 14:59 | |||||
| Dec 2, 2016 at 12:40 | history | answered | Arne Jonas Warnke | CC BY-SA 3.0 |